Differential Gene Expression in Pycnoporus coccineus during Interspecific Mycelial Interactions with Different Competitors

ABSTRACTFungi compete against each other for environmental resources. These interspecific combative interactions encompass a wide range of mechanisms. In this study, we highlight the ability of the white-rot fungusPycnoporus coccineusto quickly overgrow or replace a wide range of competitor fungi, including the gray-mold fungusBotrytis cinereaand the brown-rot fungusConiophora puteana. To gain a better understanding of the mechanisms deployed byP. coccineusto compete against other fungi and to assess whether common pathways are used to interact with different competitors, differential gene expression inP. coccineusduring cocultivation was assessed by transcriptome sequencing and confirmed by quantitative reverse transcription-PCR analysis of a set of 15 representative genes. Compared with the pure culture, 1,343 transcripts were differentially expressed in the interaction withC. puteanaand 4,253 were differentially expressed in the interaction withB. cinerea, but only 197 transcripts were overexpressed in both interactions. Overall, the results suggest that a broad array of functions is necessary forP. coccineusto replace its competitors and that different responses are elicited by the two competitors, although a portion of the mechanism is common to both. However, the functions elicited by the expression of specific transcripts appear to converge toward a limited set of roles, including detoxification of secondary metabolites.

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Adaptation of Lactobacillus plantarum IMDO 130201, a Wheat Sourdough Isolate, to Growth in Wheat Sourdough Simulation Medium at Different pH Values through Differential Gene Expression

Applied and Environmental Microbiology ◽

10.1128/aem.02668-10 ◽

2011 ◽

Vol 77 (10) ◽

pp. 3406-3412 ◽

Cited By ~ 15

Author(s):

Gino Vrancken ◽

Luc De Vuyst ◽

Tom Rimaux ◽

Joke Allemeersch ◽

Stefan Weckx

Keyword(s):

Gene Expression ◽

Lactobacillus Plantarum ◽

Differential Gene Expression ◽

Lipoteichoic Acid ◽

Low Ph ◽

Exponential Growth Phase ◽

Cellular Mechanisms ◽

Content Type ◽

Ph Values ◽

Differential Gene

ABSTRACTSourdough is a very competitive and challenging environment for microorganisms. Usually, a stable microbiota composed of lactic acid bacteria (LAB) and yeasts dominates this ecosystem. Although sourdough is rich in carbohydrates, thus providing an ideal environment for microorganisms to grow, its low pH presents a particular challenge. The nature of the adaptation to this low pH was investigated forLactobacillus plantarumIMDO 130201, an isolate from a laboratory wheat sourdough fermentation. Batch fermentations were carried out in wheat sourdough simulation medium, and total RNA was isolated from mid-exponential-growth-phase cultures, followed by differential gene expression analysis using a LAB functional gene microarray. At low pH values, an increased expression of genes involved in peptide and amino acid metabolism was found as well as that of genes involved in plantaricin production and lipoteichoic acid biosynthesis. The results highlight cellular mechanisms that allowL. plantarumto function at a low environmental pH.

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Expression of the Laccase Gene from a White Rot Fungus in Pichia pastoris Can Enhance the Resistance of This Yeast to H2O2-Mediated Oxidative Stress by Stimulating the Glutathione-Based Antioxidative System

Applied and Environmental Microbiology ◽

10.1128/aem.00218-12 ◽

2012 ◽

Vol 78 (16) ◽

pp. 5845-5854 ◽

Cited By ~ 45

Author(s):

Yang Yang ◽

Fangfang Fan ◽

Rui Zhuo ◽

Fuying Ma ◽

Yangmin Gong ◽

...

Keyword(s):

Oxidative Stress ◽

Gene Expression ◽

Pichia Pastoris ◽

Oxidative Damage ◽

White Rot ◽

Antioxidative System ◽

White Rot Fungus ◽

Laccase Gene ◽

Content Type ◽

Glutamylcysteine Synthetase

ABSTRACTLaccase is a copper-containing polyphenol oxidase that has great potential in industrial and biotechnological applications. Previous research has suggested that fungal laccase may be involved in the defense against oxidative stress, but there is little direct evidence supporting this hypothesis, and the mechanism by which laccase protects cells from oxidative stress also remains unclear. Here, we report that the expression of the laccase gene from white rot fungus inPichia pastoriscan significantly enhance the resistance of yeast to H2O2-mediated oxidative stress. The expression of laccase in yeast was found to confer a strong ability to scavenge intracellular H2O2and to protect cells from lipid oxidative damage. The mechanism by which laccase gene expression increases resistance to oxidative stress was then investigated further. We found that laccase gene expression inPichia pastoriscould increase the level of glutathione-based antioxidative activity, including the intracellular glutathione levels and the enzymatic activity of glutathione peroxidase, glutathione reductase, and γ-glutamylcysteine synthetase. The transcription of the laccase gene inPichia pastoriswas found to be enhanced by the oxidative stress caused by exogenous H2O2. The stimulation of laccase gene expression in response to exogenous H2O2stress further contributed to the transcriptional induction of the genes involved in the glutathione-dependent antioxidative system, includingPpYAP1,PpGPX1,PpPMP20,PpGLR1, andPpGSH1. Taken together, these results suggest that the expression of the laccase gene inPichia pastoriscan enhance the resistance of yeast to H2O2-mediated oxidative stress by stimulating the glutathione-based antioxidative system to protect the cell from oxidative damage.

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PADGE: analysis of heterogeneous patterns of differential gene expression

Physiological Genomics ◽

10.1152/physiolgenomics.00259.2006 ◽

2007 ◽

Vol 32 (1) ◽

pp. 154-159 ◽

Cited By ~ 15

Author(s):

Li Li ◽

Amitabha Chaudhuri ◽

John Chant ◽

Zhijun Tang

Keyword(s):

Gene Expression ◽

Differential Gene Expression ◽

Web Application ◽

Statistical Power ◽

Profile Analysis ◽

Expression Profiles ◽

Differentially Expressed ◽

Cancer Genes ◽

Data Set ◽

Differential Gene

We have devised a novel analysis approach, percentile analysis for differential gene expression (PADGE), for identifying genes differentially expressed between two groups of heterogeneous samples. PADGE was designed to compare expression profiles of sample subgroups at a series of percentile cutoffs and to examine the trend of relative expression between sample groups as expression level increases. Simulation studies showed that PADGE has more statistical power than t-statistics, cancer outlier profile analysis (COPA) (Tomlins SA, Rhodes DR, Perner S, Dhanasekaran SM, Mehra R, Sun XW, Varambally S, Cao X, Tchinda J, Kuefer R, Lee C, Montie JE, Shah RB, Pienta KJ, Rubin MA, Chinnaiyan AM. Science 310: 644–648, 2005), and kurtosis (Teschendorff AE, Naderi A, Barbosa-Morais NL, Caldas C. Bioinformatics 22: 2269–2275, 2006). Application of PADGE to microarray data sets in tumor tissues demonstrated its utility in prioritizing cancer genes encoding potential therapeutic targets or diagnostic markers. A web application was developed for researchers to analyze a large gene expression data set from heterogeneous biological samples and identify differentially expressed genes between subsets of sample classes using PADGE and other available approaches. Availability: http://www.cgl.ucsf.edu/Research/genentech/padge/ .

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Relationship of differential gene expression profiles in CD34+ myelodysplastic syndrome marrow cells to disease subtype and progression

Blood ◽

10.1182/blood-2009-08-236422 ◽

2009 ◽

Vol 114 (23) ◽

pp. 4847-4858 ◽

Cited By ~ 53

Author(s):

Kunju Sridhar ◽

Douglas T. Ross ◽

Robert Tibshirani ◽

Atul J. Butte ◽

Peter L. Greenberg

Keyword(s):

Gene Expression ◽

Acute Myeloid Leukemia ◽

Myelodysplastic Syndrome ◽

Differential Gene Expression ◽

Myeloid Leukemia ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Differentially Expressed ◽

Differential Gene ◽

Acute Myeloid

AbstractMicroarray analysis with 40 000 cDNA gene chip arrays determined differential gene expression profiles (GEPs) in CD34+ marrow cells from myelodysplastic syndrome (MDS) patients compared with healthy persons. Using focused bioinformatics analyses, we found 1175 genes significantly differentially expressed by MDS versus normal, requiring a minimum of 39 genes to separately classify these patients. Major GEP differences were demonstrated between healthy and MDS patients and between several MDS subgroups: (1) those whose disease remained stable and those who subsequently transformed (tMDS) to acute myeloid leukemia; (2) between del(5q) and other MDS patients. A 6-gene “poor risk” signature was defined, which was associated with acute myeloid leukemia transformation and provided additive prognostic information for International Prognostic Scoring System Intermediate-1 patients. Overexpression of genes generating ribosomal proteins and for other signaling pathways was demonstrated in the tMDS patients. Comparison of del(5q) with the remaining MDS patients showed 1924 differentially expressed genes, with underexpression of 1014 genes, 11 of which were within the 5q31-32 commonly deleted region. These data demonstrated (1) GEPs distinguishing MDS patients from healthy and between those with differing clinical outcomes (tMDS vs those whose disease remained stable) and cytogenetics [eg, del(5q)]; and (2) molecular criteria refining prognostic categorization and associated biologic processes in MDS.

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СONSECUTIVE INTEGRATION OF AVAILABLE MICROARRAY DATA FOR ANALYSIS OF DIFFERENTIAL GENE EXPRESSION IN HUMAN PLACENTA

Biotechnologia Acta ◽

10.15407/biotech14.01.38 ◽

2021 ◽

Vol 14 (1) ◽

pp. 38-45

Author(s):

O. Lykhenko ◽

Keyword(s):

Gene Expression ◽

Differential Gene Expression ◽

Differentially Expressed Genes ◽

Human Placenta ◽

Normal Pregnancy ◽

Integrative Analysis ◽

Differentially Expressed ◽

Second Trimester ◽

Placental Development ◽

Differential Gene

The purpose of the study was to provide the pipeline for processing of publicly available unprocessed data on gene expression via integration and differential gene expression analysis. Data collection from open gene expression databases, normalization and integration into a single expression matrix in accordance with metadata and determination of differentially expressed genes were fulfilled. To demonstrate all stages of data processing and integrative analysis, there were used the data from gene expression in the human placenta from the first and second trimesters of normal pregnancy. The source code for the integrative analysis was written in the R programming language and publicly available as a repository on GitHub. Four clusters of functionally enriched differentially expressed genes were identified for the human placenta in the interval between the first and second trimester of pregnancy. Immune processes, developmental processes, vasculogenesis and angiogenesis, signaling and the processes associated with zinc ions varied in the considered interval between the first and second trimester of placental development. The proposed sequence of actions for integrative analysis could be applied to any data obtained by microarray technology.

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Identification of gene expression alterations in C. elegans adr-2 mutants using high- throughput sequencing

Proceedings of IMPRS ◽

10.18060/23616 ◽

2019 ◽

Vol 2 (1) ◽

Author(s):

Jackson Townsend ◽

Heather A. Hundley

Keyword(s):

Gene Expression ◽

Young Adult ◽

Rna Editing ◽

Differential Gene Expression ◽

Differentially Expressed Genes ◽

High Throughput Sequencing ◽

Life Stage ◽

Differentially Expressed ◽

C Elegans ◽

Differential Gene

Background and Hypothesis: RNA editing is one of several mechanisms regulating gene expression. One type of RNA editing, the deamination of adenosine to inosine, is carried out by ADAR enzymes. ADAR enzymes are essential for neural function and aberrant editing is implicated in various forms of neuropathology. C. elegans lacking the RNA editing enzyme, ADR-2, are viable allowing us to ascertain how loss of RNA editing affects neural gene expression. The effects of loss of adr-2 on neural gene expression will be analyzed in both the first larval (L1) and young adult stages. We hypothesize that the transcriptome will change depending on life stage and the presence of ADR-2. Methods: Three replicates of neural cells isolated from wild type and adr-2(-) L1 and young adult stage animals were obtained. Total RNA was extracted from each population and mRNA was isolated using an oligo-dT bead. The mRNA was fragmented, and reverse transcribed to generate a complentary DNA (cDNA) library. The cDNA was sequenced by a facility at Indiana University. Quality of the library was evaluated using FASTqc. DE-seq2 software evaluated the differential gene expression. Results: I examined differential gene expression in two life stages of the WT and adr-2 neural samples. After obtaining the differentially expressed genes, the portions of the transcriptome that require ADR-2 was determined. WT young adults showed increased (3715) and decreased (2504) expression of neural genes when compared to the L1 stage. Many differentially expressed genes required adr-2 (~40% of the upregulated and 78% of the downregulated genes.) In addition, some genes were uniquely altered (631 upregulated, 196 downregulated) in the absence of adr-2. Conclusion and Potential Impact: The life stage and presence of ADR-2 alter the neural transcriptome and this function changes throughout development. Future studies will determine whether these genes are altered due to the lack of RNA editing or binding by ADR-2.

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Why Pashmina Goat Produces Long Hair-fiber and Barbari doesn’t: A Differential Gene Expression Study

10.20944/preprints202103.0187.v1 ◽

2021 ◽

Author(s):

Rashid Saif ◽

Tania Mahmood ◽

Aniqa Ejaz ◽

Saeeda Zia

Keyword(s):

Gene Expression ◽

Differential Gene Expression ◽

Transcriptome Assembly ◽

Hair Shaft ◽

Hair Follicles ◽

Differentially Expressed ◽

Keratinocyte Differentiation ◽

Dermal Papilla Cells ◽

Differential Gene ◽

Hair Fiber

The Pashmina and Barbari are two famous goat breeds found in the wide areas of the Indo-Pak region. Pashmina is famous for its long hair-fiber (Cashmere) production while Barbari is not-selected for this trait. So, the mRNA expression profiling in the skin samples of both breeds would be an attractive and judicious approach for detecting putative genes involved in this valued trait. Here, we performed differential gene expression analysis on publicly available RNA-Seq data from both breeds. Out of 44,617,994 filtered reads of Pashmina and 55,995,999 of Barbari which are 76.48% and 73.69% mapped to the ARS1 reference transcriptome assembly respectively. A pairwise comparison of both breeds resulted in 47,159 normalized expressed transcripts while 8,414 transcripts are differentially expressed above the significant threshold. Among these, 4,788 are upregulated in Pashmina while 3,626 transcripts are upregulated in Barbari. Fifty-nine transcripts harbor 57 genes including 32 LOC genes and 24 are annotated genes which were selected on the basis of TMM counts > 500. Genes with ectopic expressions other than uncharacterized and LOC symbol genes are Keratins (KRT) and Keratin Associated Proteins (KRTAPs), CystatinA&6, TCHH, SPRR4, PPIA, SLC25A4, S100A11, DMKN, LOR, ANXA2, PRR9 and SFN. All of these genes are likely to be involved in keratinocyte differentiation, sulfur matrix proteins, dermal papilla cells, hair follicles proliferation, hair curvature, wool fiber diameter, hair transition, hair shaft differentiation and its keratinization. These differentially expressed reported genes are critically valuable for enhancing the quality and quantity of the pashmina fiber and overall breed improvement. This study will also provide important information on hair follicle differentiation for further enrichment analyses and introducing this valued trait to other goat breeds as well.

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RNA-seq 2G: online analysis of differential gene expression with comprehensive options of statistical methods

10.1101/122747 ◽

2017 ◽

Cited By ~ 4

Author(s):

Zhe Zhang ◽

Yuanchao Zhang ◽

Perry Evans ◽

Asif Chinwalla ◽

Deanne Taylor

Keyword(s):

Gene Expression ◽

Statistical Methods ◽

Differential Gene Expression ◽

Data Distribution ◽

Differentially Expressed ◽

Rna Seq ◽

Web Portal ◽

Shiny App ◽

Resource Requirements ◽

Differential Gene

ABSTRACTRNA-seq has become the most prevalent technology for measuring genome-wide gene expression, but the best practices for processing and analysing RNA-seq data are still an open question. Many statistical methods have been developed to identify genes differentially expressed between sample groups from RNA-seq data. These methods differ by their data distribution assumptions, choice of statistical test, and computational resource requirements. Over 25 methods of differential expression detection were validated and made available through a user-friendly web portal, RNA-seq 2G. All methods are suitable for analysing differential gene expression between two groups of samples. They commonly use a read count matrix derived from RNA-seq data as input and statistically compare groups for each gene. The web portal uses a Shiny app front-end and is hosted by a cloud-based server provided by Amazon Web Service. The comparison of methods showed that the data distribution assumption is the major determinant of differences between methods. Most methods are more likely to find that longer genes are differentially expressed, which substantially impacts downstream gene set-level analysis. Combining results from multiple methods can potentially diminish this bias. RNA-seq 2G makes the analysis of RNA-seq data more accessible and efficient, and is freely available at http://rnaseq2g.awsomics.org.

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Gene Expression in Atherogenesis

Thrombosis and Haemostasis ◽

10.1055/s-0037-1616238 ◽

2001 ◽

Vol 86 (07) ◽

pp. 404-412 ◽

Cited By ~ 14

Author(s):

Houshang Monajemi ◽

E. Karin Arkenbout ◽

Hans Pannekoek

Keyword(s):

Gene Expression ◽

Endothelial Cells ◽

Smooth Muscle ◽

Transcription Factors ◽

Smooth Muscle Cells ◽

Differential Gene Expression ◽

New Technologies ◽

Muscle Cells ◽

Differentially Expressed ◽

Differential Gene

SummaryIt is conceivable that the extent and spatio-temperal expression of dozens or even a few hundred genes are significantly altered during the development and progression of atherosclerosis as compared to normal circumstances. Differential gene expression in vascular cells and in blood cells, due to gene-gene and gene-environment interactions can be considered the molecular basis for this disease. To comprehend the coherence of the complex genetic response to systemic and local atherosclerotic challenges, one needs accessible high through-put technologies to analyze a panel of differentially expressed genes and to describe the interactions between and among their gene products. Fortunately, new technologies have been developed which allow a complete inventory of differential gene expression, i.e. DD/RT-PCR, SAGE and DNA micro-array. The initial data on the application of these technologies in cardiovascular research are now being reported. This review summarizes a number of key observations. Special attention is paid to a few central transcription factors which are differentially expressed in endothelial cells, smooth muscle cells or monocytes/ macrophages. Recent data on the role of nuclear factor- B (NF-κB) and peroxisome proliferation-activating receptors (PPARs) are discussed. Like the PPARs, the NGFI-B subfamily of orphan receptors (TR3, MINOR and NOT) also belongs to the steroid/thryroid hormone receptor superfamily of transcription factors. We report that this subfamily is specifically induced in a sub-population of neointimal smooth muscle cells. Furthermore, intriguing new data implicating the Sp/XKLF family of transcription factors in cell-cell communication and maintenance of the atherogenic phenotype are mentioned. A member of the Sp/XKLF family, the shear stress-regulated lung Krüppel-like factor (LKLF) is speculated to be instrumental for the communication between endothelial cells and smooth muscle cells. Taken together, the expectation is that the fundamental knowledge obtained on atherogenesis and the data that will be acquired during the coming decade with the new, powerful high through-put methodologies will lead to novel modalities to treat patients suffering from cardiovascular disease. In view of the phenotypic changes of vascular and blood-borne cells during atherogenesis, therapeutic interventions likely will focus on reversal of an acquired phenotype by gene therapy approach or by using specific drugs which interfere with aberrant gene expression.

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Transcriptome characterization and differentially expressed genes under flooding and drought stress in the biomass grasses Phalaris arundinacea and Dactylis glomerata

Annals of Botany ◽

10.1093/aob/mcz074 ◽

2019 ◽

Vol 124 (4) ◽

pp. 717-730 ◽

Cited By ~ 1

Author(s):

Manfred Klaas ◽

Niina Haiminen ◽

Jim Grant ◽

Paul Cormican ◽

John Finnan ◽

...

Keyword(s):

Gene Expression ◽

Drought Stress ◽

Differential Gene Expression ◽

Dactylis Glomerata ◽

Phalaris Arundinacea ◽

Differentially Expressed ◽

Grass Species ◽

Reed Canary Grass ◽

Canary Grass ◽

Differential Gene

Abstract Background and Aims Perennial grasses are a global resource as forage, and for alternative uses in bioenergy and as raw materials for the processing industry. Marginal lands can be valuable for perennial biomass grass production, if perennial biomass grasses can cope with adverse abiotic environmental stresses such as drought and waterlogging. Methods In this study, two perennial grass species, reed canary grass (Phalaris arundinacea) and cocksfoot (Dactylis glomerata) were subjected to drought and waterlogging stress to study their responses for insights to improving environmental stress tolerance. Physiological responses were recorded, reference transcriptomes established and differential gene expression investigated between control and stress conditions. We applied a robust non-parametric method, RoDEO, based on rank ordering of transcripts to investigate differential gene expression. Furthermore, we extended and validated vRoDEO for comparing samples with varying sequencing depths. Key Results This allowed us to identify expressed genes under drought and waterlogging whilst using only a limited number of RNA sequencing experiments. Validating the methodology, several differentially expressed candidate genes involved in the stage 3 step-wise scheme in detoxification and degradation of xenobiotics were recovered, while several novel stress-related genes classified as of unknown function were discovered. Conclusions Reed canary grass is a species coping particularly well with flooding conditions, but this study adds novel information on how its transcriptome reacts under drought stress. We built extensive transcriptomes for the two investigated C3 species cocksfoot and reed canary grass under both extremes of water stress to provide a clear comparison amongst the two species to broaden our horizon for comparative studies, but further confirmation of the data would be ideal to obtain a more detailed picture.

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